Symmetric Seasonality of Time Series in Interval Prediction for Financial Management of the Branch

Abstract

The paper examines the task of managing the finances of a company with branches when funds are saved on the central company account, from which payments for the expenses of the branches are made. The dynamics of these expenses may have similar dynamics, which makes it possible to build a single model for the entire group. This article is devoted to the construction of theoretical concepts of the nonlinear dynamics approach and the formalization of criteria for combining time series into a single model. We introduce the concept of series with the same type of symmetrical seasonality, based on phase portraits, which allows formalizing the similarity criterion based on symmetry transformations. Considering time series that are recognized as similar, we bypass nonstationarity by considering the series included in the group as realizations of a random process. Finally, the use of new concepts allows solving an important practical problem, reducing the analysis to grouping by seasonal similarity and statistical characteristics of deviations when symmetry transformations are violated.